Time Saving
Reduce time required to analyze dynamometer cards and reliance on manual interpretation.
Dynamometer Card Diagnostic Tool
AI-powered solution designed to automate the analysis of rod pump dynamometer cards — faster, more consistent diagnostics across many wells.
More than 1,000 wells diagnosed — RodMind automates dynamometer card interpretation for rod-pump fleets at scale.
Artificial intelligence (AI) automated analysis of sucker rod pumps (SRPs) dynamometer cards allowing for faster and more consistent diagnostics across many wells via rod-lifting pump knowledge coupled with AI models. RodMind assists production teams to early identify performance issues and maintain optimum pump operation.
Surface and downhole cards are streamed in from your SCADA or controller data.
RodMind classifies each card against a dataset of all known SRP failure modes.
Production engineers receive a prioritized list of wells, root causes, and recommended actions.
Reduce time required to analyze dynamometer cards and reliance on manual interpretation.
Reduce effort required for manual interpretation, therefore reducing human errors.
Early detection of potential failures helping avoid equipment damage, reduce unplanned shutdowns and minimize production deferment.
Supports the optimization of SRPs operating parameters to improve operational efficiency and maximize production performance.
RodMind has been validated through testing with leading oil and gas companies and supported by published papers.
Incorporates huge dataset with all known SRP dynamometer card issues; streamlined processes increase job throughput.
Minimal manual interpretation and a fully automated diagnostic workflow shrank dynacard analysis from weeks to under a day.
Read Case Study →Learn how AI-driven dynacard diagnostics can cut analysis time, surface failure risks earlier, and standardize interpretation across your entire well portfolio.
Tell me more →RodMind cut our manual dynacard interpretation from days to minutes — and surfaced underperforming wells we didn't know we had.
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